• Journal of the Korean Society for Nondestructive Testing
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• v.34 no.5
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• pp.377-383
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• 2014

An addressable conducting network (ACN) makes it possible to monitor the condition of a structure using the electrical resistance between electrodes on the surface of a carbon fiber reinforced plastics (CFRP) structure. To improve the damage detection reliability of the ACN, the contact resistances between the electrodes and CFRP laminates needs to be minimized. In this study, silver nanoparticle electrodes were fabricated via printed electronics techniques on a CFRP composite. The contact resistance between the silver electrodes and CFRP were measured with respect to various fabrication conditions such as the sintering temperature of the silver nano-ink and the surface roughness of the CFRP laminates. The interfaces between the silver electrode and carbon fibers were observed using a scanning electron microscope (SEM). Based on this study, it was found that the lowest contact resistance of $0.3664{\Omega}$ could be achieved when the sintering temperature of the silver nano-ink and surface roughness were $120^{\circ}C$ and 0.230 a, respectively.

• JSTS:Journal of Semiconductor Technology and Science
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• v.14 no.2
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• pp.153-162
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• 2014

We show that carbon nanotube sensors with gold particles on the single-walled carbon nanotube (SWNT) network operate as Schottky barrier transistors, in which transistor action occurs primarily by varying the resistance of Au-SWNT junction rather than the channel conductance modulation. Transistor characteristics are calculated for the statistically simplified geometries, and the sensing mechanisms are analyzed by comparing the simulation results of the MOSFET model and Schottky junction model with the experimental data. We demonstrated that the semiconductor MOSFET effect cannot explain the experimental phenomena such as the very low limit of detection (LOD) and the logarithmic dependence of sensitivity to the DNA concentration. By building an asymmetric concentric-electrode model which consists of serially-connected segments of CNTFETs and Schottky diodes, we found that for a proper explanation of the experimental data, the work function shifts should be ~ 0.1 eV for 100 pM DNA concentration and ~ 0.4 eV for $100{\mu}M$.

• Food Science of Animal Resources
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• v.33 no.4
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• pp.463-473
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• 2013

Through the development of efficient data collecting technologies like RFID, and inter-enterprise collaboration platforms such as web services, companies which participate in supply chains can acquire visibility over the whole supply chain, and can make decisions to optimize the overall supply chain networks and processes, based on the extracted knowledge from historical data collected by the visibility system. Although not currently active, the MeatWatch system has been developed, and is used in part for this purpose, in the imported beef distribution network in Korea. However, the imported beef distribution network is too complicated to analyze its various aspects using ordinary process analysis approaches. In this paper, we suggest a novel approach, called RFID-based supply chain process mining, to automatically discover and analyze the overall supply chain processes from the distributed RFID event data, without any prior knowledge. The proposed approach was implemented and validated, by using a case study of the imported beef distribution network in Korea. Specifically we demonstrated that the proposed approach can be successfully applied to discover supply chain networks from the distributed event data, to simplify the supply chain networks, and to analyze anomaly of the distribution networks. Such novel process mining functionalities can reinforce the capability of traceability services like MeatWatch in the future.

• Journal of the Korean Society of Radiology
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• v.18 no.1
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• pp.21-26
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• 2024

The one of the famous deep learning models for object detection task is you only look once version 5 (YOLOv5) framework based on the one stage architecture. In addition, YOLOv5 model indicated high performance for accurate lesion detection using the bottleneck CSP layer and skip connection function. The purpose of this study was to evaluate the performance of YOLOv5 framework according to various hyperparameters in position emission tomogrpahy (PET) phantom images. The dataset was obtained from QIN PET segmentation challenge in 500 slices. We set the bounding box to generate ground truth dataset using labelImg software. The hyperparameters for network train were applied by changing optimization function (SDG, Adam, and AdamW), activation function (SiLU, LeakyRelu, Mish, and Hardwish), and YOLOv5 model size (nano, small, large, and xlarge). The intersection over union (IOU) method was used for performance evaluation. As a results, the condition of outstanding performance is to apply AdamW, Hardwish, and nano size for optimization function, activation function and model version, respectively. In conclusion, we confirmed the usefulness of YOLOv5 network for object detection performance in nuclear medicine images.

• Genomics & Informatics
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• v.5 no.3
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• pp.133-136
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• 2007

The Gene Set network viewer (GSnet) visualizes the functional enrichment of a given gene set with a protein interaction network and is implemented as a plug-in for the Cytoscape platform. The functional enrichment of a given gene set is calculated using a hypergeometric test based on the Gene Ontology annotation. The protein interaction network is estimated using public data. Set operations allow a complex protein interaction network to be decomposed into a functionally-enriched module of interest. GSnet provides a new framework for gene set analysis by integrating a priori knowledge of a biological network with functional enrichment analysis.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1783-1784
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• 2006

A laser interferometer is the unique measurement device that can measure the range up to a few meters with sub-nano resolution and this characteristic makes it as the important sensing device for the emerging nano-mechatronics technologies. The laser interferometer, however, is very sensitive to the environments such as temperature, humidity, sound noises, vibrations and air turbulences and these factors result in a few hundred nano meter errors. There have been many efforts to reduce these environmental errors. The output of the laser interferometer is assumed to be the sum of a real displacement and a Markov process noise. The purpose of this paper is to develop Kalman filter algorithms to reduce the laser interferometer measurement errors by exploiting the information of displacements in position-servo systems.

• Journal of the Korean Ceramic Society
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• v.39 no.4
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• pp.336-340
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• 2002

Pure and nano-sized $TiO_2$ and $CaTiO_3$ powders were fabricated by a polymeric steric entrapment route and planetary milling process. An ethylene glycol was used as a polymeric carrier for the preparation of organic-inorganic precursors. Titanium isopropoxide and calcium nitrate were dissolved in liquid-type ethylene glycol without any precipitation. At the optimum amount of the polymer, the metal cations were dispersed in solution and a homogeneous polymeric network was formed. The dried precursor ceramic gels were turned to porous powders through calcination process. The porous powders were crystallized at low temperatures and the crystalline powders were planetary milled to nano size.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.668-674
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• 2022

Machine learning techniques using visual data have high usability in fields of industry and service such as scene recognition, fault detection, security and user analysis. Among these, user analysis through the videos from CCTV is one of the practical way of using vision data. Also, many studies about lightweight artificial neural network have been published to increase high usability for mobile and embedded environment so far. In this study, we propose the network combining the object detection and classification for mobile graphic processing unit. This network detects pedestrian and face, classifies age and gender from detected face. Proposed network is constructed based on MobileNet, YOLOv2 and skip connection. Both detection and classification models are trained individually and combined as 2-stage structure. Also, attention mechanism is used to improve detection and classification ability. Nvidia Jetson Nano is used to run and evaluate the proposed system.

• 한국신재생에너지학회:학술대회논문집
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• 2006.11a
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• pp.443-446
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• 2006

Carbon-supported Platinum (Pt) is the potential electro-catalyst material for anodic and cathodic reactions in fuel cell. Catalytic activity of the metal strongly depends on the particle shape, size and distribution of the metal in the porous supportive network. Conventional preparation techniques based on wet impregnation and chemical reduction of the metal precursors often do not provide adequate control of particle size and shape. We have proposed a novel route for preparing nano sized Pt colloidal particles in solution by oxidation of ethylene glycol. These Pt nano particles were deposited on large surface area carbon support. The process of nano Pt colloid formation involves the oxidation of solvent ethylene glycol to mainly glycolic acid and the presence of its anion glycolate depends on the solution pH. In the process of colloidal Pt formation glycolate actsas stabilizer for the Pt colloidal particle and prevents the agglomeration of colloidal Pt particles. These mono disperse Pt particles in carbon support are found uniformly distributed in nearly spherical shape and the size distribution was narrow for both supported and unsupported metals. The average diameter of the Pt nano particle was controlled in the range off to 3 nm by optimizing reaction parameters. Transmission electron microscopy, CV and RRDE experiments were used to compliment the results.

• BMB Reports
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• v.44 no.1
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• pp.1-10
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• 2011

Inter-cellular communication via diffusible small molecules is a defining character not only of multicellular forms of life but also of single-celled organisms. A large number of bacterial genes are regulated by the change of chemical milieu mediated by the local population density of its own species or others. The cell density-dependent "autoinducer" molecules regulate the expression of those genes involved in genetic competence, biofilm formation and persistence, virulence, sporulation, bioluminescence, antibiotic production, and many others. Recent innovations in recombinant DNA technology and micro-/nano-fluidics systems render the genetic circuitry responsible for cell-to-cell communication feasible to and malleable via synthetic biological approaches. Here we review the current understanding of the molecular biology of bacterial intercellular communication and the novel experimental protocols and platforms used to investigate this phenomenon. A particular emphasis is given to the genetic regulatory circuits that provide the standard building blocks which constitute the syntax of the biochemical communication network. Thus, this review gives focus to the engineering principles necessary for rewiring bacterial chemo-communication for various applications, ranging from population-level gene expression control to the study of host-pathogen interactions.